Assessing cardiac function from total-variation-regularized 4D C-arm CT in the presence of angular undersampling

Time-resolved tomographic cardiac imaging using an angiographic C-arm device may support clinicians during minimally invasive therapy by enabling a thorough analysis of the heart function directly in the catheter laboratory. However, clinically feasible acquisition protocols entail a highly challeng...

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Veröffentlicht in:Physics in medicine & biology Jg. 62; H. 7; S. 2762 - 2777
Hauptverfasser: Taubmann, O, Haase, V, Lauritsch, G, Zheng, Y, Krings, G, Hornegger, J, Maier, A
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England 07.04.2017
Schlagworte:
Algorithms
Electrocardiography
Four-Dimensional Computed Tomography - methods
Heart - diagnostic imaging
Heart - physiopathology
Humans
Phantoms, Imaging
Tomography, X-Ray Computed - methods
Ventricular Function, Left
ISSN:1361-6560
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Zusammenfassung:Time-resolved tomographic cardiac imaging using an angiographic C-arm device may support clinicians during minimally invasive therapy by enabling a thorough analysis of the heart function directly in the catheter laboratory. However, clinically feasible acquisition protocols entail a highly challenging reconstruction problem which suffers from sparse angular sampling of the trajectory. Compressed sensing theory promises that useful images can be recovered despite massive undersampling by means of sparsity-based regularization. For a multitude of reasons-most notably the desired reduction of scan time, dose and contrast agent required-it is of great interest to know just how little data is actually sufficient for a certain task. In this work, we apply a convex optimization approach based on primal-dual splitting to 4D cardiac C-arm computed tomography. We examine how the quality of spatially and temporally total-variation-regularized reconstruction degrades when using as few as [Formula: see text] projection views per heart phase. First, feasible regularization weights are determined in a numerical phantom study, demonstrating the individual benefits of both regularizers. Secondly, a task-based evaluation is performed in eight clinical patients. Semi-automatic segmentation-based volume measurements of the left ventricular blood pool performed on strongly undersampled images show a correlation of close to 99% with measurements obtained from less sparsely sampled data.
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ISSN:1361-6560
DOI:10.1088/1361-6560/aa6241